Example embodiments of the inventive concepts disclosed herein relate to an image segmentation device and method for segmentation an image, and more particularly, to an image segmentation device and method based on a sequential frame image of a static scene.
An image is composed of three signals of red (R), green (G) and blue (B), and in segmenting an image, the same color region or object region is extracted from an image including an input color signal. Such image extraction data may be usefully used in fields associated with digital image processing such as image analysis and image detection for object-based image information processing. Most image region segmentation methods based on a color signal project an input color signal onto different color spaces to extract the degree of concentration thereof, or segment an image into a plurality of regions on the basis of spatial contiguity between color pixels in the image region. More specifically, as image segmentation methods, there are an edge detection segmentation method, a segmentation method using a threshold value, a segmentation method based on a region, and a segmentation method based on motion. Particularly, a region growing technique is an image segmentation method based on a region, and segments an image into a plurality of regions in a scheme that detects a seed point with respect to each region and determines whether peripheral pixels and the seed point may be included in the same region according to a relationship between the seed point and neighbor pixels thereof. In segmenting an image, however, main concern is the over-segmentation of one region. Over-segmentation denotes that an image is excessively segmented to an undesired region. To prevent such over-segmentation, it is required to set an appropriate reference for the growing and merging of regions, and simultaneously, the sizes of the regions are required to be considered. Image segmentation methods based on such region growing technique are relatively excellent in performance and simply realized, but have limitations in that it is difficult to set an accurate segmentation reference for the progressive change of brightness intensity as in a shadow portion in an actual photograph, and image segmentation is affected by noise. That is, the existing region growing technique using a single frame is vulnerable to noises. To reduce such noises, a method is used where an operation of comparing a region and a peripheral pixel uses only a statistic value based on the average of regions and a peripheral single pixel, but is insufficient to reduce noises and secure reliability.